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赵泽宇's Projects

ampligraph icon ampligraph

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

awesome-agi icon awesome-agi

AGI资料汇总学习(主要包括LLM和AIGC),持续更新......

awesome-deeplearning icon awesome-deeplearning

深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI

awesome-rlhf icon awesome-rlhf

A curated list of reinforcement learning with human feedback resources (continually updated)

bert4pytorch icon bert4pytorch

超轻量级bert的pytorch版本,大量中文注释,容易修改结构,持续更新

bigdata-interview icon bigdata-interview

:dart: :star2:[大数据面试题]分享自己在网络上收集的大数据相关的面试题以及自己的答案总结.目前包含Hadoop/Hive/Spark/Flink/Hbase/Kafka/Zookeeper框架的面试题知识总结

chatlm-mini-chinese icon chatlm-mini-chinese

中文对话0.2B小模型(ChatLM-Chinese-0.2B),开源所有数据集来源、数据清洗、tokenizer训练、模型预训练、SFT指令微调、RLHF优化等流程的全部代码。支持下游任务sft微调。

chinese-clip icon chinese-clip

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

chunkllama icon chunkllama

[ICML'24] Data and code for our paper "Training-Free Long-Context Scaling of Large Language Models"

codegeex icon codegeex

CodeGeeX: An Open Multilingual Code Generation Model

cogdl icon cogdl

CogDL: An Extensive Toolkit for Deep Learning on Graphs

colossalai icon colossalai

Making big AI models cheaper, easier, and scalable

deepctr-torch icon deepctr-torch

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

fairscale icon fairscale

PyTorch extensions for high performance and large scale training.

fe4ml-zh icon fe4ml-zh

:book: [译] 面向机器学习的特征工程

flink-recommandsystem-demo icon flink-recommandsystem-demo

:helicopter::rocket:基于Flink实现的商品实时推荐系统。flink统计商品热度,放入redis缓存,分析日志信息,将画像标签和实时记录放入Hbase。在用户发起推荐请求后,根据用户画像重排序热度榜,并结合协同过滤和标签两个推荐模块为新生成的榜单的每一个产品添加关联产品,最后返回新的用户列表。

flink-simple-tutorial icon flink-simple-tutorial

:bell::pill:flink简易使用教程,结合官方仓库的example样例,结合常见场景,使用flink的基本功能

fucking-algorithm icon fucking-algorithm

刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.

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